class_docstr: A specific binarization of the MNIST dataset.
docstr: Generate Binarized MNIST examples as dicts.
  
  Args:
    data_path (str): Path to the data files
  
  Yields:
    Generator yielding the next examples
docstr_tok: ["Generate","Binarized","MNIST","examples","as","dicts",".","Args",":","data_path","(","str",")",":","Path","to","the","data","files","Yields",":","Generator","yielding","the","next","examples"]
code: def _generate_examples(self, data_path):
      """Generate Binarized MNIST examples as dicts.
  
      Args:
        data_path (str): Path to the data files
  
      Yields:
        Generator yielding the next examples
      """
      with tf.io.gfile.GFile(data_path, "rb") as f:
          images = np.loadtxt(f, delimiter=" ", dtype=np.uint8).reshape(
              (-1,) + mnist.MNIST_IMAGE_SHAPE
          )
      for index, image in enumerate(images):
          yield index, {"image": image}
  
file_path: datasets/tensorflow_datasets/datasets/binarized_mnist/binarized_mnist_dataset_builder.py
imports: import numpy
  from six.moves import urllib
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.image_classification import mnist
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the Builder obj's underlying member method code with example usage: obj._generate_examples(data_path) without return types